Comparison
agentops vs langchain
Verdict
Pick agentops when tags unique to agentops: agent, agentops, agents-sdk, ai; pick langchain when pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI..
Markdown twin · agentops alternatives · langchain alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | agentops | langchain |
|---|---|---|
| Maintenance | Active (20d since push) As of today · github_public_v1 | Very active (0d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of 1d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of today · osv@v1 | No lockfile (source not queried) As of 4d · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- agentops
- Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and Ca
- langchain
- The agent engineering platform.
Stars
- agentops
- 5.7k
- langchain
- 142k
Forks
- agentops
- 608
- langchain
- 24k
Open issues
- agentops
- 172
- langchain
- 419
Language
- agentops
- Python
- langchain
- Python
Adopt for
- agentops
- -
- langchain
- LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect
Persona
- agentops
- -
- langchain
- -
Runtime
- agentops
- -
- langchain
- -
License
- agentops
- MIT
- langchain
- MIT License, allowing free use for both personal and commercial purposes under its stipulated terms.
Last pushed
- agentops
- Jun 25, 2026
- langchain
- Jul 14, 2026
Categories
- agentops
- AI Agents, Inference & Serving, LLM Frameworks
- langchain
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- agentops
- Active (82%)
- langchain
- Very active (96%)
Days since push
- agentops
- 20d
- langchain
- 0d
Open issues (now)
- agentops
- 172
- langchain
- 419
Full report
- agentops
- Trust report
- langchain
- Trust report
Shared compatibility
- Python · agentops: Python runtime · langchain: Python runtime
Choose agentops if…
- Tags unique to agentops: agent, agentops, agents-sdk, ai.
- Also covers Inference & Serving.
- Leaner open-issue backlog (172).
When NOT to use agentops
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Choose langchain if…
- Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI..
- Tags unique to langchain: agents, ai-agents, chatgpt, deepagents.
- * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations.
When NOT to use langchain
- * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity.
- * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth
- * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (AgentOps-AI/agentops) · observed Jul 15, 2026
- GitHub forks (AgentOps-AI/agentops) · observed Jul 15, 2026
- Last push (AgentOps-AI/agentops) · observed Jun 25, 2026
- License file (MIT) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (langchain-ai/langchain) · observed Jul 14, 2026
- GitHub forks (langchain-ai/langchain) · observed Jul 14, 2026
- Last push (langchain-ai/langchain) · observed Jul 14, 2026
- License file (MIT) · observed Jul 14, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agentops 5.7k · langchain 142k (synced Jul 15, 2026).
Common questions
- What is the difference between agentops and langchain?
- agentops: Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and Ca. langchain: The agent engineering platform.. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentops over langchain?
- Choose agentops over langchain when Tags unique to agentops: agent, agentops, agents-sdk, ai; Also covers Inference & Serving; Leaner open-issue backlog (172).
- When should I choose langchain over agentops?
- Choose langchain over agentops when Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.; Tags unique to langchain: agents, ai-agents, chatgpt, deepagents; * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations.
- When should I avoid agentops?
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- When should I avoid langchain?
- * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework.
- Is agentops or langchain more popular on GitHub?
- langchain has more GitHub stars (141,713 vs 5,710). Stars measure visibility, not whether either tool fits your constraints.
- Are agentops and langchain open source?
- Yes - both are open-source projects on GitHub (agentops: MIT, langchain: MIT).
- Where can I find alternatives to agentops or langchain?
- GraphCanon lists graph-backed alternatives at agentops alternatives and langchain alternatives (agentops markdown twin, langchain markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, agentops or langchain?
- agentops: Active. langchain: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for agentops and langchain?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentops trust report; langchain trust report.